Ontology-based faceted semantic search with automatic sense disambiguation for bioenergy domain

@article{Farazi2018OntologybasedFS,
  title={Ontology-based faceted semantic search with automatic sense disambiguation for bioenergy domain},
  author={Feroz Farazi and Craig B. Chapman and Pathmeswaran Raju and Lynsey Melville},
  journal={Int. J. Big Data Intell.},
  year={2018},
  volume={5},
  pages={62-72}
}
WordNet is a lexicon widely known and used as an ontological resource hosting comparatively large collection of semantically interconnected words. Use of such resources produces meaningful results and improves users' search experience through the increased precision and recall. This paper presents our facet-enabled WordNet powered semantic search work done in the context of the bioenergy domain. The main hurdle to achieving the expected result was sense disambiguation further complicated by the… 

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References

SHOWING 1-10 OF 40 REFERENCES

Ontology Driven Semantic Search

This paper proposes a search engine based on web resource semantics that is semantically annotated using an existing open semantic elaboration platform and an ontology is used to describe the knowledge domain into which perform queries.

Clever Search: A WordNet Based Wrapper for Internet Search Engines

An approach to enhance search engines with information about word senses available in WordNet is presented, which exploits information about the conceptual relations within the lexical-semantic net.

Semantic Search Meets the Web

A novel semantic search system that provides the user with the capability to query Semantic Web information using natural language by means of an ontology-based Question Answering (QA) system and complements the specific answers retrieved during the QA process with a ranked list of documents from the Web.

WordNet: A Lexical Database for English

WordNet1 provides a more effective combination of traditional lexicographic information and modern computing, and is an online lexical database designed for use under program control.

A WordNet-based Query Expansion Method for Geographical Information Retrieval

This report describes a query expansion method based on the expansion of geographical terms by means of WordNet synonyms and meronyms. We used this method for our participation to the GeoCLEF 2005

Yago: a core of semantic knowledge

YAGO builds on entities and relations and currently contains more than 1 million entities and 5 million facts, which includes the Is-A hierarchy as well as non-taxonomic relations between entities (such as HASONEPRIZE).

Revising the Wordnet Domains Hierarchy: semantics, coverage and balancing

This paper presents the WordNet Domains Hierarchy (WDH), a language-independent resource composed of 164, hierarchically organized, domain labels, and illustrates a new version of WDH addressing problems by an explicit and systematic reference to the Dewey Decimal Classification.

Conceptual Graph Matching for Semantic Search

This paper proposes an approach for semantic search by matching conceptual graphs by calculating semantic similarities between concepts, relations and conceptual graphs using the detailed definitions of semantic similarity.

SemSearch: A Search Engine for the Semantic Web

SemSearch is presented, a search engine, which pays special attention to semantic search by providing several means to hide the complexity of semantic search from end users and thus make it easy to use and effective.

Toward a semantic search engine based on ontologies

In this framework, a search request is first processed by a query parser which then finds qualified RDF triples in domain ontologies, and an extended term-document matrix is built to reflect the relevance between documents, concepts/individuals, and terms.